Building upon the three established paradigms of science that have lead to many technological advances over time: experimental, theoretical and simulation-based, a fourth “data-driven“ paradigm of science is emerging today using machine learning and the large amounts of experimental and simulation-data available [1]}. “Big-data” science unifies the first three paradigms and opens up new avenues in materials science under the umbrella term of materials informatics. The field of material informatics is very new and many unsolved questions still remain open and wait for proper answers [2]}.
